{"id":"W2021035803","doi":"10.1287/opre.1110.0937","title":"Multiple Variable Proportionality in Data Envelopment Analysis","year":2011,"lang":"en","type":"article","venue":"Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Data envelopment analysis; Proportionality (law); Bundle; Returns to scale; Variable (mathematics); Envelopment; Computer science; Econometrics; Set (abstract data type); Operations research; Mathematics; Mathematical optimization; Economics; Microeconomics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02899996,0.002453092,0.002838953,0.004841358,0.001100506,0.005323265,0.001999859,0.002341438,0.001988315],"category_scores_gemma":[0.05545409,0.001328273,0.002782962,0.0103601,0.003530923,0.005122392,0.003891296,0.004904852,0.0006307674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004169864,"about_ca_system_score_gemma":0.00347478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004854178,"about_ca_topic_score_gemma":0.002390726,"domain_scores_codex":[0.9673027,0.02155338,0.002002376,0.002684281,0.005773913,0.0006833839],"domain_scores_gemma":[0.9721737,0.02256719,0.001495037,0.001712689,0.001873804,0.0001775804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004168823,0.00005975357,0.001318114,0.000439664,0.0002433823,0.0001667292,0.0002802152,0.3388719,0.000579407,0.5883673,0.001257753,0.06837406],"study_design_scores_gemma":[0.00001526583,0.00005148923,0.0005724317,0.000170522,0.00004713769,0.00007814218,0.00008907332,0.5524374,0.001177452,0.4347669,0.01051367,0.00008053476],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002040745,0.002143276,0.9929972,0.0002942324,0.00004786531,0.00007516946,0.00006547149,0.00004650042,0.002289564],"genre_scores_gemma":[0.2464695,0.0077528,0.7412164,0.0002647477,0.0002989351,0.0009775329,0.0003281734,0.0001528665,0.002539091],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02899996,"threshold_uncertainty_score":0.1533682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6788556956010486,"score_gpt":0.5484107332782845,"score_spread":0.1304449623227641,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}